Frequent downregulation of LRRC26 by epigenetic alterations is involved in the malignant progression of triple-negative breast cancer

Transcriptome analysis in various cell lines exposed to nitric oxide

Nitric oxide (NO) plays a physiological role in signal transduction and excess or chronic NO has toxic effects as an inflammatory mediator. NO reversibly forms protein S-nitrosylation and exerts toxicological functions related to disease progression. DNA methyltransferases, epigenome-related enzymes, are inhibited in enzymatic activity by S-nitrosylation. Therefore, excess or chronic NO exposure may cause disease by altering gene expression. However, the effects of chronic NO exposure on transcriptome are poorly understood. Here, we performed transcriptome analysis of A549, AGS, HEK293T, and SW48 cells exposed to NO (100 μM) for 48 hr. We showed that the differentially expressed genes were cell-specific. Gene ontology analysis showed that the functional signature of differentially expressed genes related to cell adhesion or migration was upregulated in several cell lines. Gene set enrichment analysis indicated that NO stimulated inflammation-related gene expression in various cell lines. This finding supports previous studies showing that NO is closely involved in inflammatory diseases. Overall, this study elucidates the pathogenesis of NO-associated inflammatory diseases by focusing on changes in gene expression.

Distinctive Properties of Endothelial Cells from Tumor and Normal Tissue in Human Breast Cancer

Tumor microenvironments shape aggressiveness and are largely maintained by the conditions of angiogenesis formation. Thus, endothelial cells’ (ECs) biological reactions are crucial to understand and control the design of efficient therapies. In this work, we used models of ECs to represent a breast cancer tumor site as well as the same, healthy tissue. Cells characterization was performed at the transcriptome and protein expression levels, and the cells functional biological responses (angiogenesis and permeability) were assessed. We showed that the expression of proteins specific to ECs (ACE+, VWF+), their differentiation (CD31+, CD 133+, CD105+, CD34-), their adhesion properties (ICAM-1+, VCAM-1+, CD62-L+), and their barrier formation (ZO-1+) were all downregulated in tumor-derived ECs. NGS-based differential transcriptome analysis confirmed CD31-lowered expression and pointed to the increase of Ephrin-B2 and SNCAIP, indicative of dedifferentiation. Functional assays confirmed these differences; angiogenesis was impaired while permeability increased in tumor-derived ECs, as further validated by the distinctly enhanced VEGF production in response to hypoxia, reflecting the tumor conditions. This work showed that endothelial cells differed highly significantly, both phenotypically and functionally, in the tumor site as compared to the normal corresponding tissue, thus influencing the tumor microenvironment.

Massive parallel sequencing in a family with rectal cancer

Background

We have previously reported a family with a suspected autosomal dominant rectal and gastric cancer syndrome without any obvious causative genetic variant. Here, we focused the study on a potentially isolated rectal cancer syndrome in this family.

Methods

We included seven family members (six obligate carriers). Whole-exome sequencing and whole-genome sequencing data were analyzed and filtered for shared coding and splicing sequence and structural variants among the affected individuals.

Results

When considering family members with rectal cancer or advanced adenomas as affected, we found six new potentially cancer-associated variants in the genes CENPB, ZBTB20, CLINK, LRRC26, TRPM1, and NPEPL1. All variants were missense variants and none of the genes have previously been linked to inherited rectal cancer. No structural variant was found.

Conclusion

By massive parallel sequencing in a family suspected of carrying a highly penetrant rectal cancer predisposing genetic variant, we found six genetic missense variants with a potential connection to the rectal cancer in this family. One of them could be a high-risk genetic variant, or one or more of them could be low risk variants. The p.(Glu438Lys) variant in the CENPB gene was found to be of particular interest. The CENPB protein binds DNA and helps form centromeres during mitosis. It is involved in the WNT signaling pathway, which is critical for colorectal cancer development and its role in inherited rectal cancer needs to be further examined.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13053-021-00181-2.

High dimensional model representation of log likelihood ratio: binary classification with SNP data

BACKGROUND

Developing binary classification rules based on SNP observations has been a major challenge for many modern bioinformatics applications, e.g., predicting risk of future disease events in complex conditions such as cancer. Small-sample, high-dimensional nature of SNP data, weak effect of each SNP on the outcome, and highly non-linear SNP interactions are several key factors complicating the analysis. Additionally, SNPs take a finite number of values which may be best understood as ordinal or categorical variables, but are treated as continuous ones by many algorithms.

METHODS

We use the theory of high dimensional model representation (HDMR) to build appropriate low dimensional glass-box models, allowing us to account for the effects of feature interactions. We compute the second order HDMR expansion of the log-likelihood ratio to account for the effects of single SNPs and their pairwise interactions. We propose a regression based approach, called linear approximation for block second order HDMR expansion of categorical observations (LABS-HDMR-CO), to approximate the HDMR coefficients. We show how HDMR can be used to detect pairwise SNP interactions, and propose the fixed pattern test (FPT) to identify statistically significant pairwise interactions.

RESULTS

We apply LABS-HDMR-CO and FPT to synthetically generated HAPGEN2 data as well as to two GWAS cancer datasets. In these examples LABS-HDMR-CO enjoys superior accuracy compared with several algorithms used for SNP classification, while also taking pairwise interactions into account. FPT declares very few significant interactions in the small sample GWAS datasets when bounding false discovery rate (FDR) by 5%, due to the large number of tests performed. On the other hand, LABS-HDMR-CO utilizes a large number of SNP pairs to improve its prediction accuracy. In the larger HAPGEN2 dataset FTP declares a larger portion of SNP pairs used by LABS-HDMR-CO as significant.

CONCLUSION

LABS-HDMR-CO and FPT are interesting methods to design prediction rules and detect pairwise feature interactions for SNP data. Reliably detecting pairwise SNP interactions and taking advantage of potential interactions to improve prediction accuracy are two different objectives addressed by these methods. While the large number of potential SNP interactions may result in low power of detection, potentially interacting SNP pairs, of which many might be false alarms, can still be used to improve prediction accuracy.

Emerging roles for multifunctional ion channel auxiliary subunits in cancer

Several superfamilies of plasma membrane channels which regulate transmembrane ion flux have also been shown to regulate a multitude of cellular processes, including proliferation and migration. Ion channels are typically multimeric complexes consisting of conducting subunits and auxiliary, non-conducting subunits. Auxiliary subunits modulate the function of conducting subunits and have putative non-conducting roles, further expanding the repertoire of cellular processes governed by ion channel complexes to processes such as transcellular adhesion and gene transcription. Given this expansive influence of ion channels on cellular behaviour it is perhaps no surprise that aberrant ion channel expression is a common occurrence in cancer. This review will focus on the conducting and non-conducting roles of the auxiliary subunits of various Ca2+, K+, Na+ and Cl- channels and the burgeoning evidence linking such auxiliary subunits to cancer. Several subunits are upregulated (e.g. Cavβ, Cavγ) and downregulated (e.g. Kvβ) in cancer, while other subunits have been functionally implicated as oncogenes (e.g. Navβ1, Cavα2δ1) and tumour suppressor genes (e.g. CLCA2, KCNE2, BKγ1) based on in vivo studies. The strengthening link between ion channel auxiliary subunits and cancer has exposed these subunits as potential biomarkers and therapeutic targets. However further mechanistic understanding is required into how these subunits contribute to tumour progression before their therapeutic potential can be fully realised.